Micro - electro - mechanical system (MEMS) based accelerometers are now frequently used in many different parts of our day - to - day lives. It is also increasingly being used for structural testing applications. Researchers have had res ervation of using these devices as they are relatively untested, but now with the wider adoption, it provides a much cheaper and more versatile tool for structural engineering researchers. A number of damaged buildings in the Christchurch Central Business District (CBD) were instrumented with a number of low - cost MEMS accelerometers after the major Christchurch earthquakes. The accelerometers captured extremely high quality building response data as the buildings experienced thousands of aftershocks. This d ata set was amongst one of only a handful of data set s available around the world which provides building response data subjected to real ground motion. Furthermore, due to technological advances, a much larger than usual number of accelerometers has been deployed making the data set one of the most comprehensive available. This data set is utilised to extract modal parameters of the buildings. This paper summarises the operating requirements and preference for using such accelerometers for experimental mod al analysis. The challenges for adapting MEMS based devices for successful modal parameters identification are also discussed
Livelihood holds the key to a rapid recovery following a large-scale devastating disaster, building its resilience is of paramount importance. While much attention has been given to how to help people who are displaced from their jobs to regain employment, little research on livelihood resilience has been undertaken for those relocated communities following a disaster event. By studying five re-located villages post-2004 Indian Ocean Tsunami in Banda Aceh and Aceh Besar, Indonesia, this research has identified the indicators of livelihood resilience and the critical factors driving it for post-disaster relocated communities. A mixed approach, combining questionnaire surveys, semistructured interviews, and field observations, was used for the collection of data. Housing entitlement, the physical and mental health of residents, access to external livelihood support and the provision of infrastructure and basic services were identified as amongst the most critical indicators that represent the level of livelihood resilience. Early recovery income support, physical and mental health, availability and timeliness of livelihood support, together with cultural sensitivity and governance structure, are amongst the most important factors. Given the nature of resettlement, access to infrastructure, location of relocated sites, the safety of the neighbourhood and the ability to transfer to other jobs/skills also play an important role in establishing sustained employment for relocated communities in Indonesia. Those indicators and factors were synthesised into a framework which was further tested in the recovery of Christchurch, and Kaikoura, New Zealand during their recovery from devastating earthquakes. It is suggested that the framework can be used by government agencies and aid organisations to assess the livelihood resilience of post-disaster relocated communities. This will help better them plan support policies and/or prioritise resilience investment strategies to ensure that the recovery needs of those relocated are best met
